The neuroscience of active learning and direct instruction

• Published in: Neuroscience and biobehavioral reviews Vol. 163; p. 105737
• Main Authors: Dubinsky, Janet M., Hamid, Arif A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01-08-2024
• Subjects: Agency; Cognitive control; Intrinsic reward; Motivation; Neurobiology of learning and memory; Neuroeducation; Reinforcement learning; Science of learning; Structure learning; Student-centered learning; Teacher-centered learning; Working memory; Structure learning; Agency; Motivation; Neurobiology of learning and memory; Teacher-centered learning; Reinforcement learning; Student-centered learning; Science of learning; Working memory; Neuroeducation; Cognitive control; Intrinsic reward; student-centered learning; cognitive control; agency; neuroeducation; intrinsic reward; science of learning; working memory; motivation; neurobiology of learning and memory; teacher-centered learning; structure learning; reinforcement learning
• DOI: 10.1016/j.neubiorev.2024.105737
• EISSN: 1873-7528
• ISSN: 0149-7634; 1873-7528

Throughout the educational system, students experiencing active learning pedagogy perform better and fail less than those taught through direct instruction. Can this be ascribed to differences in learning from a neuroscientific perspective? This review examines mechanistic, neuroscientific evidence that might explain differences in cognitive engagement contributing to learning outcomes between these instructional approaches. In classrooms, direct instruction comprehensively describes academic content, while active learning provides structured opportunities for learners to explore, apply, and manipulate content. Synaptic plasticity and its modulation by arousal or novelty are central to all learning and both approaches. As a form of social learning, direct instruction relies upon working memory. The reinforcement learning circuit, associated agency, curiosity, and peer-to-peer social interactions combine to enhance motivation, improve retention, and build higher-order-thinking skills in active learning environments. When working memory becomes overwhelmed, additionally engaging the reinforcement learning circuit improves retention, providing an explanation for the benefits of active learning. This analysis provides a mechanistic examination of how emerging neuroscience principles might inform pedagogical choices at all educational levels.
•Synaptic plasticity and its modulation are foundational for epistemic learning.•Direct instruction passively describes content. Active learning leverages agency.•Agency, novelty, curiosity, social exchange, and self-evaluation improve retention.•The best educational pedagogies engage the reinforcement learning circuit.•The benefits of active learning may accrue from the reinforcement learning circuit.